In this paper, we present a comprehensive survey on applications of Support Vector
Machines (SVMs) for pattern recognition. Since SVMs show good generalization …

The problem of scarcity of labeled pixels, required for segmentation of remotely sensed
satellite images in supervised pixel classification framework, is addressed in this article. A …

In this paper, we present a survey on pattern recognition applications of Support Vector
Machines (SVMs). Since SVMs show good generalization performance on many real-life …

This valuable text addresses different pattern recognition (PR) tasks in a unified framework
with both theoretical and experimental results. Tasks covered include data condensation …

SVMs (support vector machines) suffer from the problem of large memory requirement and
CPU time when trained in batch mode on large data sets. We overcome these limitations …

The support vector machine (SVM) method, as a promising classification technique, has
been widely used in various fields due to its high efficiency. However, SVM cannot …

The paper describes a probabilistic active learning strategy for support vector machine
(SVM) design in large data applications. The learning strategy is motivated by the statistical …

We present an approach for customized heartbeat classification of electrocardiogram (ECG)
signals, based on the construction of one general multi-class classifier and one specific two …

This paper proposes a new incremental learning approach to endow a Takagi-Sugeno-type
fuzzy classification model with high generalization ability. The proposed fuzzy model is …

In the conventional incremental training of support vector machines, candidates for support
vectors tend to be deleted if the separating hyperplane rotates as the training data are …